A quantum neural network (QNN) is a parameterized mapping efficiently
im...
Quantum Hamiltonian simulation, which simulates the evolution of quantum...
Gradient descent is a fundamental algorithm in both theory and practice ...
Many quantum programs are assured by formal verification, but such
verif...
The emergence of variational quantum applications has led to the develop...
We formulate the first differentiable analog quantum computing framework...
The Variational Quantum Eigensolver (VQE) is a promising candidate for
q...
Quantum computing technology may soon deliver revolutionary improvements...
Quantum algorithms often apply classical operations, such as arithmetic ...
We investigate the algebraic reasoning of quantum programs inspired by t...
Quantum Neural Networks (QNNs), or the so-called variational quantum
cir...
We investigate sublinear classical and quantum algorithms for matrix gam...
In a recent breakthrough, Mahadev constructed a classical verification o...
Variational Quantum Circuits (VQCs), or the so-called quantum
neural-net...
We present VOQC, the first fully verified compiler for quantum circuits,...
The study of quantum generative models is well-motivated, not only becau...
Estimating the volume of a convex body is a central problem in convex
ge...
We present sqire, a low-level language for quantum computing and
verific...
We investigate quantum algorithms for classification, a fundamental prob...
Quantum computation is a topic of significant recent interest, with prac...
While recent work suggests that quantum computers can speed up the solut...